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Acknowledgements

PuReMD : A Reactive ( ReaxFF ) Molecular Dynamics Package Ananth Grama and Metin Aktulga ayg@cs.purdue.edu. Acknowledgements. Rajiv Kalia , Aiichiro Nakano, Priya Vashishtha (USC) Adri van Duin (Penn State) Steve Plimpton, Aidan Thompson (Sandia) US Department of Energy

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Acknowledgements

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  1. PuReMD: A Reactive (ReaxFF) Molecular Dynamics PackageAnanthGrama and MetinAktulgaayg@cs.purdue.edu.

  2. Acknowledgements • Rajiv Kalia, Aiichiro Nakano, PriyaVashishtha (USC) • Adri van Duin (Penn State) • Steve Plimpton, Aidan Thompson (Sandia) • US Department of Energy • US National Science Foundation

  3. Outline • Sequential Realization: SerialReax • Algorithms and Numerical Techniques • Validation • Performance Characterization • Parallel Realization: PuReMD • Parallelization: Algorithms and Techniques • Performance and Scalability • Applications • Strain Relaxation in Si/Ge/Si Nanobars • Water-Silica Interface • Oxidative Stress in Lipid Bilayers

  4. SerialReax Components System Geometry Control Parameters Force Field Parameters Program Log File System Status Update Trajectory Snapshots SerialReax • Initialization • Read input data • Initialize data structs • Neighbor Generation • 3D-grid based O(n) neighbor generation • Several optimizations for improved performance • Reallocate • Fully dynamic and adaptive memory management: • efficient use of resources • large systems on a single processor • Init Forces • Initialize the QEq coef matrix • Compute uncorr. bond orders • Generate H-bond lists • QEq • Large sparse linear system • PGMRES(50) or PCG • ILUT-based pre-conditioners • give good performance Compute Bonds Corrections are applied after all uncorrected bonds are computed • Bonded Interactions • Bonds • Lone pairs • Over/UnderCoord • Valence Angles • Hydrogen Bonds • Dihedral/ Torsion • vd Waals & electrostatics • Single pass over the • far nbr-list after • charges are updated • Interpolation with cubic • splines for nice speed-up • Evolve the System • Ftotal = Fnonbonded + Fbonded • Update x & v with velocity Verlet • NVE, NVT and NPT ensembles

  5. Linear Solver for Charge Equilibration • QEq Method: used for equilibrating charges • original QEq paper cited 600+ times • approximation for distributing partial charges • solution using Lagrange multipliers yields • N = # of atoms • H: NxN sparse matrix • s & t fictitious charges: used to determine the actual charge qi • Too expensive for direct methods  Iterative (Krylov sub-space) methods

  6. Basic Solvers for QEq • Sample systems • bulk water: 6540 atoms, liquid • lipid bilayer system: 56,800 atoms, biological system • PETN crystal: 48,256 atoms, solid • Solvers: CG and GMRES • H has heavy diagonal:diagonal pre-conditioning • slowly evolving environment : extrapolation from prev. solutions • Poor Performance: # of iterations = # of matrix-vector multiplications actual running time in seconds fraction of total computation time tolerance level = 10-6 which is fairly satisfactory due to cache effects much worse at 10-10 tolerance level more pronounced here

  7. ILU-based preconditioning • ILU-based pre-conditioners: no fill-in, 10-2 drop tolerance • effective (considering only the solve time) • no fill-in + threshold: nice scaling with system size • ILU factorization is expensive bulk water system cache effects are still evident bilayer system

  8. ILU-based preconditioning Observation: can amortize the ILU factorization cost slowly changing simulation environment re-usable pre-conditioners PETN crystal: solid, 1000s of steps! Bulk water: liquid, 10-100s of steps!

  9. Validation Hexane (C6H14) Structure Comparison Excellent agreement!

  10. Comparison to MD Methods • Comparisons using hexane: systems of various sizes • Ab-initio MD: CPMD • Classical MD: GROMACS • ReaxFF: SerialReax

  11. Comparison to LAMMPS-ReaxF Time per time-step comparison Qeq solver performance Memory foot-print • different QEq formulations • similar results • LAMMPS: • CG / no preconditioner

  12. Outline • Sequential Realization: SerialReax • Algorithms and Numerical Techniques • Validation • Performance Characterization • Parallel Realization: PuReMD • Parallelization: Algorithms and Techniques • Performance and Scalability • Applications • Strain Relaxation in Si/Ge/Si Nanobars • Water-Silica Interface • Oxidative Stress in Lipid Bilayers

  13. Parallelization: Outer-Shell r r r r/2 b b b b full shell half shell midpoint-shell tower-plate shell

  14. Parallelization: Outer-Shell choose full-shell due to dynamic bonding despite the comm. overhead r r r r/2 b b b b full shell half shell midpoint-shell tower-plate shell

  15. Parallelization: Boundary Interactions rshell= MAX (3xrbond_cut, rhbond_cut, rnonb_cut)

  16. Parallelization: Messaging

  17. Parallelization: Messaging Performance Performance Comparison: PuReMD with direct vs. staged messaging

  18. Parallelization: Optimizations • Truncate bond related computations • double computation of bonds at the outer-shell • hurts scalability as the sub-domain size shrinks • trim all bonds that are further than 3 hops or more • Scalable parallel solver for the QEq problem • GMRES/ILU factorization: not scalable • use CG + diagonal pre-conditioning • good initial guess: • redundant computations: to avoid reverse communication • iterate both systems together

  19. PuReMD: Performance and Scalability • Weak scaling test • Strong scaling test • Comparison to LAMMPS-REAX • Platform: Hera cluster at LLNL • 4 AMD Opterons/node -- 16 cores/node • 800 batch nodes – 10800 cores, 127 TFLOPS/sec • 32 GB memory / node • Infiniband interconnect • 42nd on TOP500 list as of Nov 2009

  20. PuReMD: Weak Scaling Bulk Water: 6540 atoms in a 40x40x40 A3 box / core

  21. PuReMD: Weak Scaling QEq Scaling Efficiency

  22. PuReMD: Strong Scaling Bulk Water: 52320 atoms in a 80x80x80 A3 box

  23. PuReMD: Strong Scaling Efficiency and throughput

  24. Outline • Sequential Realization: SerialReax • Algorithms and Numerical Techniques • Validation • Performance Characterization • Parallel Realization: PuReMD • Parallelization: Algorithms and Techniques • Performance and Scalability • Validation Applications • Strain Relaxation in Si/Ge/Si Nanobars • Water-Silica Interface • Oxidative Stress in Lipid Bilayers

  25. PureMD/Reax/C User Community

  26. [001], Vertical Si/Ge/Si nanoscale bars Si Ge Height (H) Si Periodic boundary conditions Width (W) [010] , Longitudinal [100], Transverse • Motivation • Si/Ge/Si nanobars: ideal for MOSFETs • as produced: biaxial strain, desirable: uniaxial • design & production: understanding strain behavior is important Related publication: Strain relaxation in Si/Ge/Si nanoscale bars from molecular dynamics simulations Y. Park, H.M. Aktulga, A.Y. Grama, A. Strachan Journal of Applied Physics 106, 1 (2009)

  27. Si/Ge/Si nanoscale bars Si Ge Si W = 20.09 nm Key Result: When Ge section is roughly square shaped, it has almost uniaxial strain! average strains for Si&Ge in each dimension average transverse Ge strain Simple strain model derived from MD results

  28. Water-Silica Interface • Motivation • a-SiO2: widely used in nano-electronic devices • also used in devices for in-vivo screening • understanding interaction with water: critical for reliability of devices Related publication: A Reactive Simulation of the Silica-Water Interface J. C. Fogarty, H. M. Aktulga, A. van Duin, A. Y. Grama, S. A. Pandit Journal of Chemical Physics 132, 174704 (2010)

  29. Water-Silica Interface Water model validation Silica model validation

  30. Water-Silica Interface Key Result Silica surface hydroxylation as evidenced by experiments is observed. Water Silica Proposed reaction: H2O + 2Si + O  2SiOH H O H O Si O

  31. Water-Silica Interface Key Result Hydrogen penetration is observed: some H atoms penetrate through the slab. Ab-initio simulations predict whole molecule penetration. We propose: water is able to diffuse through a thin film of silica via hydrogen hopping, i.e., rather than diffusing as whole units, water molecules dissociate at the surface, and hydrogens diffuse through, combining with other dissociated water molecules at the other surface.

  32. Oxidative Damage in Lipid Bilayers Motivation Modeling reactive processes in biological systems ROS Oxidative stress Cancer & Aging System Preparation 200 POPC lipid + 10,000 water molecules and same system with 1% H2O2 mixed Mass Spectograph: Lipid molecule weighs 760 u Key Result Oxidative damage observed: In pure water: 40% damaged In 1% peroxide: 75% damaged

  33. Conclusions • An efficient and scalable realization of ReaxFF through use of algorithmic and numerical techniques • Detailed performance characterization; comparison to other methods • Applications on various systems • LAMMPS/Reax/C and PuReMD strand-alone Reax implementations available over the public domain. • BUT! • Lots needs to be done – the parallel qEq is the current bottleneck • Use alternate factorizations that parallelize well (SPIKE) • GPU implementation forthcoming.

  34. References • Reactive Molecular Dynamics: Numerical Methods and Algorithmic Techniques • H. M. Aktulga, S. A. Pandit, A. C. T. van Duin, A. Y. Grama • SIAM Journal on Scientific Computing, to appear, 2011. • Parallel Reactive Molecular Dynamics: Numerical Methods and Algorithmic Techniques • H. M. Aktulga, J. C. Fogarty, S. A. Pandit, A. Y. Grama • Parallel Computing, to appear, 2011. • Strain relaxation in Si/Ge/Si nanoscale bars from molecular dynamics simulations • Y. Park, H.M. Aktulga, A.Y. Grama, A. Strachan • Journal of Applied Physics 106, 1 (2009) • A Reactive Simulation of the Silica-Water Interface • J. C. Fogarty, H. M. Aktulga, A. van Duin, A. Y. Grama, S. A. Pandit • Journal of Chemical Physics 132, 174704 (2010)

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